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LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

"""
The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.
@karpathy
"""
import os # os.path.exists
import math # math.log, math.exp
/*
* Copyright (c) 1995, 2013, Oracle and/or its affiliates. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* - Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
*
@onekung
onekung / Antigravity404
Last active May 2, 2026 05:47
Fix google Antigravity (Remote SSH on macOS: Fixing "posix_spawnp failed" and 404 Download Errors)
## Troubleshooting Antigravity Remote SSH on macOS: Fixing "posix_spawnp failed" and 404 Download Errors
When attempting to use **Antigravity** (or similar IDEs) to connect via Remote-SSH to a macOS (Darwin) server, you might encounter a `posix_spawnp failed` error or a `404 Not Found` during the server installation phase. This usually happens because the official `darwin-arm` server binary is missing from the download mirrors.
Below is a verified workaround to manually "assemble" a working Remote Server by bridging the Linux-arm structure with native Darwin binaries.
### 🛠 Prerequisites
On your **Remote macOS Server**, ensure you have the necessary tools installed via Homebrew:
@rohitg00
rohitg00 / llm-wiki.md
Last active May 2, 2026 05:44 — forked from karpathy/llm-wiki.md
LLM Wiki v2 — extending Karpathy's LLM Wiki pattern with lessons from building agentmemory

LLM Wiki v2

A pattern for building personal knowledge bases using LLMs. Extended with lessons from building agentmemory, a persistent memory engine for AI coding agents.

This builds on Andrej Karpathy's original LLM Wiki idea file. Everything in the original still applies. This document adds what we learned running the pattern in production: what breaks at scale, what's missing, and what separates a wiki that stays useful from one that rots.

What the original gets right

The core insight is correct: stop re-deriving, start compiling. RAG retrieves and forgets. A wiki accumulates and compounds. The three-layer architecture (raw sources, wiki, schema) works. The operations (ingest, query, lint) cover the basics. If you haven't read the original, start there.